weka.classifiers.meta
Class CostSensitiveClassifier

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.meta.CostSensitiveClassifier

All Implemented Interfaces:

java.lang.Cloneable, Drawable, OptionHandler, java.io.Serializable

public class CostSensitiveClassifier

extends Classifier

implements OptionHandler, Drawable

This metaclassifier makes its base classifier cost-sensitive. Two methods can be used to introduce cost-sensitivity: reweighting training instances according to the total cost assigned to each class; or predicting the class with minimum expected misclassification cost (rather than the most likely class).

Valid options are:

-M
Minimize expected misclassification cost. (default is to reweight training instances according to costs per class)

-W classname
Specify the full class name of a classifier (required).

-C cost file
File name of a cost matrix to use. If this is not supplied, a cost matrix will be loaded on demand. The name of the on-demand file is the relation name of the training data plus ".cost", and the path to the on-demand file is specified with the -N option.

-N directory
Name of a directory to search for cost files when loading costs on demand (default current directory).

-S seed
Random number seed used when reweighting by resampling (default 1).

Options after -- are passed to the designated classifier.

Version:

$Revision: 1.18 $

Author:

Len Trigg (len@reeltwo.com)

See Also:

Serialized Form

Field Summary

protected Classifier	m_Classifier The classifier
protected java.lang.String	m_CostFile The name of the cost file, for command line options
protected CostMatrix	m_CostMatrix The cost matrix
protected int	m_MatrixSource Indicates the current cost matrix source
protected boolean	m_MinimizeExpectedCost True if the costs should be used by selecting the minimum expected cost (false means weight training data by the costs)
protected java.io.File	m_OnDemandDirectory The directory used when loading cost files on demand, null indicates current directory
protected int	m_Seed Seed for reweighting using resampling.
static int	MATRIX_ON_DEMAND
static int	MATRIX_SUPPLIED
static Tag[]	TAGS_MATRIX_SOURCE

Fields inherited from class weka.classifiers.Classifier

m_Debug

Fields inherited from interface weka.core.Drawable

BayesNet, NOT_DRAWABLE, TREE

Constructor Summary

CostSensitiveClassifier()

Method Summary

void	buildClassifier(Instances data) Builds the model of the base learner.
java.lang.String	classifierTipText()
java.lang.String	costMatrixSourceTipText()
java.lang.String	costMatrixTipText()
double[]	distributionForInstance(Instance instance) Returns class probabilities.
Classifier	getClassifier() Gets the classifier used.
protected java.lang.String	getClassifierSpec() Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier
CostMatrix	getCostMatrix() Gets the misclassification cost matrix.
SelectedTag	getCostMatrixSource() Gets the source location method of the cost matrix.
boolean	getMinimizeExpectedCost() Gets the value of MinimizeExpectedCost.
java.io.File	getOnDemandDirectory() Returns the directory that will be searched for cost files when loading on demand.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
int	getSeed() Get seed for resampling.
java.lang.String	globalInfo()
java.lang.String	graph() Returns graph describing the classifier (if possible).
int	graphType() Returns the type of graph this classifier represents.
java.util.Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(java.lang.String[] argv) Main method for testing this class.
java.lang.String	minimizeExpectedCostTipText()
java.lang.String	onDemandDirectoryTipText()
java.lang.String	seedTipText()
void	setClassifier(Classifier classifier) Sets the distribution classifier
void	setCostMatrix(CostMatrix newCostMatrix) Sets the misclassification cost matrix.
void	setCostMatrixSource(SelectedTag newMethod) Sets the source location of the cost matrix.
void	setMinimizeExpectedCost(boolean newMinimizeExpectedCost) Set the value of MinimizeExpectedCost.
void	setOnDemandDirectory(java.io.File newDir) Sets the directory that will be searched for cost files when loading on demand.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setSeed(int seed) Set seed for resampling.
java.lang.String	toString() Output a representation of this classifier

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

MATRIX_ON_DEMAND

public static final int MATRIX_ON_DEMAND

See Also:

Constant Field Values

MATRIX_SUPPLIED

public static final int MATRIX_SUPPLIED

See Also:

Constant Field Values

TAGS_MATRIX_SOURCE

public static final Tag[] TAGS_MATRIX_SOURCE

m_MatrixSource

protected int m_MatrixSource

Indicates the current cost matrix source

m_OnDemandDirectory

protected java.io.File m_OnDemandDirectory

The directory used when loading cost files on demand, null indicates current directory

m_CostFile

protected java.lang.String m_CostFile

The name of the cost file, for command line options

m_CostMatrix

protected CostMatrix m_CostMatrix

The cost matrix

m_Classifier

protected Classifier m_Classifier

The classifier

m_Seed

protected int m_Seed

Seed for reweighting using resampling.

m_MinimizeExpectedCost

protected boolean m_MinimizeExpectedCost

True if the costs should be used by selecting the minimum expected cost (false means weight training data by the costs)

Constructor Detail

CostSensitiveClassifier

public CostSensitiveClassifier()

Method Detail

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class Classifier

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options. Valid options are:

-M
Minimize expected misclassification cost. (default is to reweight training instances according to costs per class)

-W classname
Specify the full class name of a classifier (required).

-C cost file
File name of a cost matrix to use. If this is not supplied, a cost matrix will be loaded on demand. The name of the on-demand file is the relation name of the training data plus ".cost", and the path to the on-demand file is specified with the -N option.

-N directory
Name of a directory to search for cost files when loading costs on demand (default current directory).

-S seed
Random number seed used when reweighting by resampling (default 1).

Options after -- are passed to the designated classifier.

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class Classifier

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the Classifier.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class Classifier

Returns:

an array of strings suitable for passing to setOptions

globalInfo

public java.lang.String globalInfo()

Returns:

a description of the classifier suitable for displaying in the explorer/experimenter gui

costMatrixSourceTipText

public java.lang.String costMatrixSourceTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getCostMatrixSource

public SelectedTag getCostMatrixSource()

Gets the source location method of the cost matrix. Will be one of MATRIX_ON_DEMAND or MATRIX_SUPPLIED.

Returns:

the cost matrix source.

setCostMatrixSource

public void setCostMatrixSource(SelectedTag newMethod)

Sets the source location of the cost matrix. Values other than MATRIX_ON_DEMAND or MATRIX_SUPPLIED will be ignored.

Parameters:

newMethod - the cost matrix location method.

onDemandDirectoryTipText

public java.lang.String onDemandDirectoryTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getOnDemandDirectory

public java.io.File getOnDemandDirectory()

Returns the directory that will be searched for cost files when loading on demand.

Returns:

The cost file search directory.

setOnDemandDirectory

public void setOnDemandDirectory(java.io.File newDir)

Sets the directory that will be searched for cost files when loading on demand.

Parameters:

newDir - The cost file search directory.

minimizeExpectedCostTipText

public java.lang.String minimizeExpectedCostTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getMinimizeExpectedCost

public boolean getMinimizeExpectedCost()

Gets the value of MinimizeExpectedCost.

Returns:

Value of MinimizeExpectedCost.

setMinimizeExpectedCost

public void setMinimizeExpectedCost(boolean newMinimizeExpectedCost)

Set the value of MinimizeExpectedCost.

Parameters:

newMinimizeExpectedCost - Value to assign to MinimizeExpectedCost.

classifierTipText

public java.lang.String classifierTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setClassifier

public void setClassifier(Classifier classifier)

Sets the distribution classifier

Parameters:

classifier - the classifier with all options set.

getClassifier

public Classifier getClassifier()

Gets the classifier used.

Returns:

the classifier

getClassifierSpec

protected java.lang.String getClassifierSpec()

Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier

Returns:

the classifier string.

costMatrixTipText

public java.lang.String costMatrixTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getCostMatrix

public CostMatrix getCostMatrix()

Gets the misclassification cost matrix.

Returns:

the cost matrix

setCostMatrix

public void setCostMatrix(CostMatrix newCostMatrix)

Sets the misclassification cost matrix.

seedTipText

public java.lang.String seedTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setSeed

public void setSeed(int seed)

Set seed for resampling.

Parameters:

seed - the seed for resampling

getSeed

public int getSeed()

Get seed for resampling.

Returns:

the seed for resampling

buildClassifier

public void buildClassifier(Instances data)
                     throws java.lang.Exception

Builds the model of the base learner.

Specified by:

buildClassifier in class Classifier

Parameters:

data - the training data

Throws:

java.lang.Exception - if the classifier could not be built successfully

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception

Returns class probabilities. When minimum expected cost approach is chosen, returns probability one for class with the minimum expected misclassification cost. Otherwise it returns the probability distribution returned by the base classifier.

Overrides:

distributionForInstance in class Classifier

Parameters:

instance - the instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction

Throws:

java.lang.Exception - if instance could not be classified successfully

graphType

public int graphType()

Returns the type of graph this classifier represents.

Specified by:

graphType in interface Drawable

Returns:

the type of graph representing the object

graph

public java.lang.String graph()
                       throws java.lang.Exception

Returns graph describing the classifier (if possible).

Specified by:

graph in interface Drawable

Returns:

the graph of the classifier in dotty format

Throws:

java.lang.Exception - if the classifier cannot be graphed

toString

public java.lang.String toString()

Output a representation of this classifier

main

public static void main(java.lang.String[] argv)

Main method for testing this class.

Parameters:

argv - should contain the following arguments: -t training file [-T test file] [-c class index]